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Pain Prediction Via Machine Learning: Electrical Thresholds and Interoception

1 novembre 2026 mis à jour par: Aybike Senel, Amasya University

Machine Learning-Based Pain Prediction in University Students: Electrical Threshold Measurements and Interoception

The goal of this observational study is to predict (retrospective and prospective) musculoskeletal pain in university students using machine learning models based on electrical threshold measurements and interoceptive awareness. The main question it aims to answer is:

Can electrical sensory, motor, and pain thresholds, along with interoceptive awareness scores, predict musculoskeletal pain status in young adults using machine learning algorithms?

Participants will:

Complete demographic, healthy lifestyle (physical activity, sitting time, meal frequency), and substance use (ASSIST v3.0) questionnaires.

Complete self-report surveys including the Nordic Musculoskeletal Questionnaire (NMQ) and the Multidimensional Assessment of Interoceptive Awareness (MAIA-2).

Undergo quantitative electrical threshold testing on their dominant hand, which includes 3 consecutive measurements of sensory threshold, motor threshold (after a 10-minute rest), and pain threshold (after another 10-minute rest).

Aperçu de l'étude

Statut

Pas encore de recrutement

Les conditions

Description détaillée

The aim of this study is to investigate the relationship between musculoskeletal pain, electrical threshold values, and interoception in healthy university students, and to evaluate the predictive accuracy of machine learning models for both retrospective and prospective musculoskeletal pain.

Designed as an observational, analytical, and cross-sectional study with a prospective follow-up component, this study will include approximately 550 healthy, right-hand dominant students aged 18-25 who provide written informed consent.

Participants' demographic data and healthy lifestyle behaviors (physical activity, sitting time, nutrition, and tobacco/alcohol/substance use via ASSIST) will be recorded. Musculoskeletal complaints will be evaluated using the Nordic Musculoskeletal Questionnaire, and interoception will be assessed using the Multidimensional Assessment of Interoceptive Awareness-II. Finally, electrical sensory, motor, and pain thresholds will be measured using a combined electrotherapy device with electrodes placed over the flexor muscles of the forearm. One week later, participants will be contacted again to re-evaluate their pain complaints during the preceding 7 days.

In statistical analyses, in addition to correlation and regression analyses among parameters, the performance of three machine learning models-Logistic Regression, Random Forest, and XGBoost-in predicting participants' retrospective and prospective pain will be evaluated.

The research results will demonstrate several key outcomes. First, they will elucidate the relationship between musculoskeletal pain, electrical threshold values, and interoception in university students, while testing the utility of electrical threshold values as an objective tool in musculoskeletal pain assessment. Furthermore, the study will evaluate the accuracy of machine learning models in predicting both retrospective and prospective pain within this population. By leveraging objective measurements obtained from widely accessible clinical devices, the findings will contribute to digital health approaches and applications that guide researchers and clinicians throughout pain evaluation and treatment processes. Ultimately, this work will provide critical insights into the efficacy of the proposed research methodology before its implementation in diverse patient populations.

Type d'étude

Observationnel

Inscription (Estimé)

550

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

  • Nom: Aybike Şenel, Assistant Professor
  • Numéro de téléphone: +90 531 583 99 24
  • E-mail: aybikesenel@hotmail.com

Lieux d'étude

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

18 ans à 25 ans (Adulte)

Accepte les volontaires sains

Oui

Sexes éligibles pour l'étude

Tout

Méthode d'échantillonnage

Échantillon non probabiliste

Population étudiée

University students with healthy lifestyle

La description

Inclusion criteria:

  • Being healthy and aged 18-25
  • Having the right hand as the dominant extremity
  • Being able to communicate effectively and understand the study procedure
  • Being willing to participate in the study and having signed the written informed consent

Exclusion criteria:

  • Presence of continuous or periodic pain in the same region over the last 3 months (presence of chronic pain)
  • Presence of sleep problems
  • History of severe menstrual or abdominal pain
  • Diagnosis of an endocrinological, psychiatric, urogenital, neurological, dermatological, cardiorespiratory, or musculoskeletal disease and/or sleep disorder that could be related to the study outcomes
  • Being pregnant or the possibility of pregnancy

Criteria for withdrawal from the study:

  • Deciding not to participate in the study and not wishing to complete the assessments
  • Experiencing discomfort due to the assessments and measurements and not wishing to complete them

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

  • Modèles d'observation: COHORT
  • Perspectives temporelles: PROSPECTIVE

Cohortes et interventions

Groupe / Cohorte
Intervention / Traitement
university students with healthy lifestyle

No Intervention: Observational Cohort

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Retrospective Pain
Délai: baseline

Self-reported musculoskeletal pain presence and anatomical localization over the preceding 12 months and past 7 days, assessed using the Nordic Musculoskeletal Questionnaire (NMQ). The NMQ is a standardized screening instrument that evaluates musculoskeletal symptoms (pain, ache, or discomfort) across 9 distinct body regions (neck, shoulders, elbows, wrists/hands, upper back, lower back, hips/thighs, knees, and ankles/feet).

baseline
Prospective Pain
Délai: 1 week post-baseline

Presence and anatomical site of self-reported prospective musculoskeletal pain or discomfort experienced during the 1-week follow-up period. Participants will be re-evaluated via a structured telephone or digital questionnaire inquiring about any newly developed or ongoing musculoskeletal pain symptoms in the preceding 7 days. Pain presence is recorded as a binary outcome (Yes/No) for overall pain and for specific body regions.

1 week post-baseline
Electrical Sensory, Motor, and Pain Thresholds
Délai: baseline

Quantitative evaluation of somatosensory processing using a standardized monochromatic combined electrotherapy device (Intelect Advanced Monochromatic Combo). Electrodes 5x5 cm will be placed over the wrist flexor muscles on the anterior aspect of the dominant forearm using a symmetric biphasic square wave (100 Hz frequency, 100 µs phase duration, current increased at a rate of 1 mA/s). Three threshold parameters will be measured in milliamperes (mA):Electrical Sensory Threshold (EST): The minimum current intensity at which the participant first perceives a tingling or sensory stimulus.Electrical Motor Threshold (EMT): The minimum current intensity required to elicit a visible muscle contraction.Electrical Pain Threshold (EPT): The minimum current intensity at which the electrical sensation first becomes painful.

baseline
Interoceptive Awareness
Délai: baseline

Multidimensional self-reported interoceptive bodily awareness assessed using the Multidimensional Assessment of Interoceptive Awareness-2 (MAIA-2) scale. The MAIA-2 is a 37-item questionnaire evaluated on a 6-point Likert scale (0= Never to 5=Always) across 8 distinct subscales: Noticing, Not-Distracting, Not-Worrying, Attention Regulation, Emotional Awareness, Self-Regulation, Body Listening, Trust.

Subscale scores are calculated as the mean of their respective items (range: 0 to 5), with higher scores indicating higher levels of interoceptive awareness.

baseline

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Parrainer

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Estimé)

1 décembre 2026

Achèvement primaire (Estimé)

1 janvier 2028

Achèvement de l'étude (Estimé)

1 janvier 2028

Dates d'inscription aux études

Première soumission

19 septembre 2026

Première soumission répondant aux critères de contrôle qualité

19 septembre 2026

Première publication (Réel)

24 septembre 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

3 novembre 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

1 novembre 2026

Dernière vérification

1 octobre 2026

Plus d'information

Termes liés à cette étude

Plan pour les données individuelles des participants (IPD)

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Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

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